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Official implementation of NanoNet: Real-time medical Image segmentation architecture (IEEE CBMS)

Home Page: https://arxiv.org/abs/2104.11138

Python 100.00%

unet medical-image-segmentation nanonets polyp-segmentation residual-networks squeeze-and-excitation python segmentation tensorflow capsule-endoscopy

nanonet's Introduction

Hi there 👋

We are looking self-motivated researcher to join our team to advance the field of Artificial Intelligence in Medicine.

nanonet's People

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scott-mao cvlinks kelkalot enoch-chen reshalfahsi lesotlhok zhxu7000 wqiiqw

nanonet's Issues

Issue about residual_block

Hi,

Thank you for your great job. However, I have a question about the "residual block", as shown in follow, is it suppose to use x_init?

NanoNet/model.py

Line 25 in 7a7c9fe

s = Conv2D(num_filters, (1, 1), padding="same")(x)

Mingtao
Best regards

Error while compiling to edgetpu model

Hello,
I want to run this model in edgetpu, I converted the TensorFlow model to TFLite with posttraining quantization and after this when i try to convert tflite quantized model to edgetpu using edgetpu compiler, I am getting the following error:

Edge TPU Compiler version 16.0.384591198 Started a compilation timeout timer of 180 seconds. ERROR: Attempting to use a delegate that only supports static-sized tensors with a graph that has dynamic-sized tensors. Compilation failed: Model failed in Tflite interpreter. Please ensure model can be loaded/run in Tflite interpreter. Compilation child process completed within timeout period. Compilation failed!

I don't understand this error, please help me to solve this error

Thanks & Regards,
Pratik Patel

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